AnyStory: Towards Unified Single and Multiple Subject Personalization in Text-to-Image Generation
V2.0.0
Official demo of AnyStory 2 🤗. We will continuously update this demo.
For technical details, please refer to our tech report: AnyStory: Towards Unified Single and Multiple Subject Personalization in Text-to-Image Generation. 😊
🚀🚀🚀 Quick Start:
1. Upload subject reference images (clean background; real human IDs unsupported for now), Add prompts (only EN supported), and Click "RUN".
2. (Recommended) Click "Segment Subject" to create masks (or upload your own B&W masks) for subjects. This helps the model better reference the subject you specify (otherwise, we will perform automatic detection). 🤗
💡💡💡 Tips:
If the subject doesn't appear, try adding a detailed description of the subject in the prompt that matches the reference image, and avoid conflicting details (e.g., significantly altering the subject's appearance). Multi-subject referencing in AnyStory2 is still being optimized. 🤗
1. Upload subject reference images (clean background; real human IDs unsupported for now), Add prompts (only EN supported), and Click "RUN".
2. (Recommended) Click "Segment Subject" to create masks (or upload your own B&W masks) for subjects. This helps the model better reference the subject you specify (otherwise, we will perform automatic detection). 🤗
💡💡💡 Tips:
If the subject doesn't appear, try adding a detailed description of the subject in the prompt that matches the reference image, and avoid conflicting details (e.g., significantly altering the subject's appearance). Multi-subject referencing in AnyStory2 is still being optimized. 🤗
Examples
| Subject [A] Reference Image | Subject [A] Mask (upload supported) | Subject [B] Reference Image | Subject [B] Mask (upload supported) | Prompt | Generated Image |
|---|
More examples: Intelligent creation of AI story pictures integrated with Qwen Agent
📝 Citation
If our work is helpful for your research or applications, please cite us via:
@article{he2025anystory,
title={AnyStory: Towards Unified Single and Multiple Subject Personalization in Text-to-Image Generation},
author={He, Junjie and Tuo, Yuxiang and Chen, Binghui and Zhong, Chongyang and Geng, Yifeng and Bo, Liefeng},
journal={arXiv preprint arXiv:2501.09503},
year={2025}
}
If you have any questions, feel free to open an issue or contact us directly at hejunjie1103@gmail.com.